NEED TO USE PANDAS AND SCIKIT-LEARN LIBRARIES!!

Case Study:

Predict whether or not it will rain tomorrow by training a binary classification model on target column RainTomorrow. You are provided dataset that contains daily weather observations from numerous Australian weather stations. This dataset is from Kaggle.com

The target RainTomorrow means: Did it rain the next day? Yes or No.

Note: You should exclude the variable RISK_MM when training your binary classification model. If you don't exclude it, you will leak the answers to your model and reduce its predictability. Read more about it here the dataset creator has provided an explanation for need to exclude RISK_MM

Assignment Tasks:

The goal is to build a binary classification model to predict if it will rain tomorrow given the input variables. Here are some guidelines to consider for modeling binary classification use case:

• Experiment with Feature Engineering and check if it helps with model performance
• Experiment with multiple Classification models
• Use various model evaluation matrices (including ROC Curve & AUC) to compare performance of various experiments